In digital communication systems, since data is generally transmitted over a limited band, interference is occurred in adjacent symbols due to a time dispersion effect that allows pulse energy of symbols to be dispersed into adjacent symbol pulses. Besides, data transmitted is affected by a variety of channel distortions. This channel distortion phenomenon contains multi-path phenomenon, frequency offset, phase jitter and so on. These phenomenons cause InterSymbol Interference (ISI), implying that transmission symbols affect adjacent symbols in digital communication systems, which becomes a great obstacle in obtaining required data.
In order to decrease symbol errors caused by such ISI, a conventional receiver (for example, digital broadcasting receiver) employs a channel equalization apparatus.
In most communication channels, since distortion factors as mentioned above are variable, they adopt an adaptive equalizer which adaptively updates tap coefficients according to time.
Hereinafter, a description will be given on a configuration of a conventional channel equalizer with reference to FIG. 1.
FIG. 1 illustrates a configuration of a general Decision Feedback Equalization (DFE) device.
As illustrated therein, in the general DFE device, a digital filter 11 removes ISI components that introduce distortions in a baseband signal received by a receiver (digital broadcasting receiver). At a symbol detector (simple quantizer) 12, a signal from the digital filter 11 is compared with a preset threshold to produce decision data.
Inputs to a tap coefficient updater 13 are an output signal of an equalizer input signal storage unit 17, an output signal of the digital filter 11, and error data selected by a switch 16, wherein an error is computed to update tap coefficients of the digital filter 11.
At a training sequence storage unit 14, a training data sequence that is also known by a transmitter (digital broadcasting transmitter) is stored therein. This training data sequence is read out in a training mode and provided to the tap coefficient updater 13.
At a statistical data calculator 15, a statistical error is calculated in a blind mode and forwarded to the tap coefficient updater 13.
At the switch 16, one of the outputs from the training sequence storage unit 14, the statistical data calculator 15 and the symbol detector 12 is selected in response to a selected mode and provided to the tap coefficient updater 13 as error data.
Then, at the tap coefficient updater 13, a corresponding error signal is derived; and then data corresponding to the tap coefficients of the digital filter 11 is read out from the equalizer input signal storage unit 17 to update the tap coefficients. The updated tap coefficients are then delivered to the digital filter 11.
As the channel equalization device, the DFE device is widely used in digital broadcasting receivers. Typically, the DFE device has a structure that an eye diagram of its output is open, which serves to precisely and easily do output signal decision as performance decision factor of the equalization device. Therefore, if an output of the symbol detector is a correctly decided symbol, a feedback filter has an advantage in that it does not involve any problem such as noise amplification phenomenon at output of the filter caused by a linear equalizer during the channel equalization while removing ISI by a previously decided symbol.
To make this merit of the DFE device useful, it is important not to raise decision error at an output of the symbol detector. Above all things, it is important to open the eye diagram of equalization device output.
For the above purpose, in Advanced Television System Committee (ATSC) digital broadcasting system that is American-type terrestrial TV standard, there is used a method that inserts one training sequence segment every 312 data segments to open the eye diagram of the equalization device output while suffering from reduction in data efficiency, wherein one segment is 208 bytes.
However, there exist many cases that it fails to open the eye diagram of the filter output since the inserted training sequence is short under a multi-path environment with a long ghost. Further, under a poor multi-path environment with insufficient tap coefficients of the filter in length for their convergence although the training sequence is existed, time-variable channel varied according to time, long ghost, or ghost with large signal level, there are many cases that it fails to open the eye diagram of the filter output. If the eye diagram is not open, there is a very high possibility that raises decision error in the symbol detector. This brings about an error propagation problem that allows error decision to be accumulated through the feedback loop of the DFE device.
Therefore, in order to make the tap coefficients of the filter converged or track time-variable channel properly, there is required a method of reducing decision error even during a data interval with no training sequence. In the absence of training sequence, an output of the symbol detector should be used in place of the training sequence. Thus, it needs to reduce total tap energy of feedback filter to minimize any effect by decision error of the symbol detector.
Most of conventional methods of decreasing such a decision error employ a Viterbi decoder with decoding delay. Typically, there is a method which gives a same delay as a decoding delay of the Viterbi decoder in an equalizer tap coefficient adjustor. This is disclosed in G. Long's proposal, entitled “The LMS Algorithm with Delayed Coefficient Adaptation”, IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-37, October 1989.
Another method solves the decoding delay of the Viterbi decoder by adding a periodical interleaver and deinterleaver thereto. This method is provided in M. V. Eyuboglu's proposal, entitled “Detection of Coded Modulation Signals on Linear, Severely Distorted Channels Using Decision-Feedback Noise Prediction with Interleaving”, IEEE Trans. Commu., vol. COM-36, pp. 401-409, April 1988. An additional method is disclosed in U.S. Pat. No. 4,833,693 issued to Eyuboglu.
The conventional methods of decreasing such a decision error as mentioned above adopt the Viterbi decoder with decoding delay value of (TBD-1) following the DFE device as the symbol detector thereof; and thus, they need additional devices to remove the decoding delay. Moreover, those methods require that TBD should be at least 5 times a value with one more than the number of memories of Trellis encoder used for a coding process for the Viterbi decoder following the equalization device to have a sufficiently good performance.
Normally, however, the decoding delay should be small maximally in order to use the output of the Viterbi decoder as feedback input of the DFE device.
In particular, as shown in FIG. 5, the decoding delay value becomes 12× (TBD-1), rather than (TBD-1), in digital broadcasting systems adopting 12 Trellis Coded Modulation (TCM) encoders by Trellis code interleaver; and approximate decoding delay value becomes 168 because the number of memories of TCM encoder is 2. It is not very efficient to apply the Viterbi decoder with such a decoding delay value to actual systems.
Therefore, to use Viterbi decoder as the symbol detector of the DFE device in the digital broadcasting systems, the decoding delay should be small maximally, wherein it is of course the best to have no decoding delay.
Meanwhile, as existing methods of decreasing tap energy of the feedback filter, there are methods which increase tap number of feedforward filter that removes a post ghost, and change channel characteristic of received signal by making an antenna beam-forming or using a channel matched filter.
The method of increasing the tap number of the feedforward filter is known to be inefficient and performance improvement is lowered compared with an increased amount of tap number. Further, the method of changing the channel characteristic using the channel matched filter has relatively good performance compared with the method of increasing the tap number. This is disclosed in Richard Citta's suggestion, entitled “A VSB Receiver Designed for Indoor and Distributed Transmission Environments”, IEEE 52nd Annual Broadcast Symposium, Oct. 9-11, 2002.
The channel equalization method suggested by Richard Citta has a very high degree of complexity since it provides a channel matched filter using over-sampled data and employs a fractionally-spaced equalization device. Furthermore, since such a method utilizes a simple quantizer (slicer) as a symbol detector, there may be occurred an error propagation problem by decision error.
To improve the Richard Citta's method, another method is issued for a method of using a channel matched filter and an equalization device of symbol unit with low degree of complexity and an implementation method of a symbol detector with small decision error. This method is proposed by Hyeung-Nam Kim, Seoung-Ik Park, Seung-Won Kim, entitled “Performance Improvement of Channel Equalization in Terrestrial DTV Receivers using Channel Estimation”, Signal Processing Symposium, vol. 16, no. 1, pp. 176, September 2003.
This method improves stability of convergence but has a disadvantage in that the length of a pre ghost is long due to use of the channel matched filter, thereby causing a residual mean square error after convergence to be larger than a case with no channel matched filter rather.
Consequently, as one solution of the above problems, there has been a need for development of a filter capable of changing channel more mildly by changing a pre ghost to a post ghost.